An image registration algorithm based on mutual information maximization and non-linear diffusion is presented. It relies on a non-parametric estimation of the degree of dependency between the reference image and the template to be registered, which is intrinsically more robust against possible deformations due to imaging geometry and propagation disturbances. The approach based on non linear diffusion, nonetheless, has the advantage of producing a non-parametric discrete warping model which does not rely on a particular set of basis functions, and is therefore as much general as possible. The experimental results on simulated images have quantitatively shown the accuracy of the proposed method.

An image registration algorithm based on mutual information maximization and non-linear diffusion is presented. It relies on a non-parametric estimation of the degree of dependency between the reference image and the template to be registered, which is intrinsically more robust against possible deformations due to imaging geometry and propagation disturbances. The approach based on non linear diffusion, nonetheless, has the advantage of producing a non-parametric discrete warping model which does not rely on a particular set of basis functions, and is therefore as much general as possible. The experimental results on simulated images have quantitatively shown the accuracy of the proposed method.

Image registration using non-linear diffusion

Ceccarelli M;Di Bisceglie M;Galdi C;Ullo S
2008

Abstract

An image registration algorithm based on mutual information maximization and non-linear diffusion is presented. It relies on a non-parametric estimation of the degree of dependency between the reference image and the template to be registered, which is intrinsically more robust against possible deformations due to imaging geometry and propagation disturbances. The approach based on non linear diffusion, nonetheless, has the advantage of producing a non-parametric discrete warping model which does not rely on a particular set of basis functions, and is therefore as much general as possible. The experimental results on simulated images have quantitatively shown the accuracy of the proposed method.
978-142442808-3
An image registration algorithm based on mutual information maximization and non-linear diffusion is presented. It relies on a non-parametric estimation of the degree of dependency between the reference image and the template to be registered, which is intrinsically more robust against possible deformations due to imaging geometry and propagation disturbances. The approach based on non linear diffusion, nonetheless, has the advantage of producing a non-parametric discrete warping model which does not rely on a particular set of basis functions, and is therefore as much general as possible. The experimental results on simulated images have quantitatively shown the accuracy of the proposed method.
image registration; smoothing methods ; remote sensing
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.12070/11154
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